Response of Spectral Reflectances and Vegetation Indices on Varying Juniper Cone Densities

Juniper trees are widely distributed throughout the world and are common sources of allergies when microscopic pollen grains are transported by wind and inhaled. In this study, we investigated the spectral influences of pollen-discharging male juniper cones within a juniper canopy. This was done through a controlled outdoor experiment involving ASD FieldSpec Pro Spectroradiometer measurements over juniper canopies of varying cone densities. Broadband and narrowband spectral reflectance and vegetation index (VI) patterns were evaluated as to their sensitivity and their ability to discriminate the presence of cones. The overall aim of this research was to assess remotely sensed phenological capabilities to detect pollen-bearing juniper trees for public health applications. A general decrease in reflectance values with increasing juniper cone density was found, particularly in the Green (545–565 nm) and NIR (750–1,350 nm) regions. In contrast, reflectances in the shortwave-infrared (SWIR, 2,000 nm to 2,350 nm) region decreased from no cone presence to intermediate amounts (90 g/m2) and then increased from intermediate levels to the highest cone densities (200 g/m2). Reflectance patterns in the Red (620–700 nm) were more complex due to shifting contrast patterns in absorptance between cones and juniper foliage, where juniper foliage is more absorbing than cones only within the intense narrowband region of maximum chlorophyll absorption near 680 nm. Overall, narrowband reflectances were more sensitive to cone density changes than the equivalent MODIS broadbands. In all VIs analyzed, there were significant relationships with cone density levels, particularly with the narrowband versions and the two-band vegetation index (TBVI) based on Green and Red bands, a promising outcome for the use of phenocams in juniper phenology trait studies. These results indicate that spectral indices are sensitive to certain juniper phenologic traits that can potentially be used for juniper cone detection in support of public health applications.

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